Abstract
A model is proposed for predicting the result of a football match from the previous results of both teams. This model underlies the method of identifying nonlinear dependencies by fuzzy knowledge bases. Acceptable simulation results can be obtained by tuning fuzzy rules using tournament data. The tuning procedure implies choosing the parameters of fuzzy-term membership functions and rule weights by a combination of genetic and neural optimization techniques.
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Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 171–184, July–August 2005.
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Rotshtein, A.P., Posner, M. & Rakityanskaya, A.B. Football Predictions Based on a Fuzzy Model with Genetic and Neural Tuning. Cybern Syst Anal 41, 619–630 (2005). https://doi.org/10.1007/s10559-005-0098-4
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DOI: https://doi.org/10.1007/s10559-005-0098-4